IoT Goes Nuclear: Creating a Zigbee Chain Reaction
Eyal Ronen (Weizmann Institute of Science)
Presented at the
2017 IEEE Symposium on Security & Privacy
May 22–24, 2017
San Jose, CA
http://www.ieee-security.org/TC/SP2017/
ABSTRACT
Within the next few years, billions of IoT devices will densely populate our cities. In this paper we describe a new type of threat in which adjacent IoT devices will infect each other with a worm that will rapidly spread over large areas, provided that the density of compatible IoT devices exceeds a certain critical mass. In particular, we developed and verified such an infection using the popular Philips Hue smart lamps as a platform. The worm spreads by jumping directly from one lamp to its neighbors, using only their built-in ZigBee wireless connectivity and their physical proximity. The attack can start by plugging in a single infected bulb anywhere in the city, and then catastrophically spread everywhere within minutes. It enables the attacker to turn all the city lights on or off, to permanently brick them, or to exploit them in a massive DDOS attack. To demonstrate the risks involved, we use results from percolation theory to estimate the critical mass of installed devices for a typical city such as Paris whose area is about 105 square kilometers: The chain reaction will fizzle if there are fewer than about 15,000 randomly located smart lamps in the whole city, but will spread everywhere when the number exceeds this critical mass (which had almost certainly been surpassed already). To make such an attack possible, we had to find a way to remotely yank already installed lamps from their current networks, and to perform over-the-air firmware updates. We overcame the first problem by discovering and exploiting a major bug in the implementation of the Touchlink part of the ZigBee Light Link protocol, which is supposed to stop such attempts with a proximity test. To solve the second problem, we developed a new version of a side channel attack to extract the global AES-CCM key (for each device type) that Philips uses to encrypt and authenticate new firmware. We used only readily available equipment costing a few hundred dollars, and managed to find this key without seeing any actual updates. This demonstrates once again how difficult it is to get security right even for a large company that uses standard cryptographic techniques to protect a major product.

Evaluate now- get the LaunchPad development kit
http://www.ti.com/tool/launchxl-cc3235s
This week on Connect, Andrew, a SimpleLink product marketing engineer,
answers some commonly asked questions from the Connect [1]community around
the new dual-band (2.4 GHz + 5-GHz) [2] SimpleLink Wi-Fi wireless MCUs and
how you can get better performance while maintaining excellent power
consumption with 5-GHz.
The dual-band CC3235x device comes in two variants, CC3235S and C3235SF:
* The CC3235S [3] includes 256KB of RAM, IoT networking security, device
identity/keys, as well as, MCU level security features such as file system
encryption, user IP (MCU image) encryption, secure boot and debug
security.
* The CC3235SF [4] builds on the CC3235S and integrates a user-dedicated
1MB of executable flash in addition to the 256KB of RAM.
These devices are also offered as fully programmable FCC, ISED/IC, ETSI/CE,
and MIC CERTIFIED wireless microcontroller modules.
[1] https://www.youtube.com/playlist?index=1&amp;playnext=1&amp;list=PLISmVLHAZbTSwxYATL2RBGtMreIp0iHf3
[2] http://ti.com/product/cc3235s
[3] http://www.ti.com/product/cc3235s
[4] http://www.ti.com/product/cc3235sf
Learn more about SimpleLink Wi-Fi SoCs
http://www.ti.com/wireless-connectivity/simplelink-solutions/wi-fi/overview/overview.html
100% Code Portability with SimpleLink MCUs
http://www.ti.com/wireless-connectivity/simplelink-solutions/overview/overview.html
Subscribe to Connect, a weekly series
https://www.youtube.com/playlist?index=1&playnext=1&list=PLISmVLHAZbTSwxYATL2RBGtMreIp0iHf3

Secure Thingz provides solutions to build security into the core of IoT connected devices for critical infrastructure, industrial, automotive and other markets, and
we also aim to help engineers understand the processes used in securing their applications. In this webinar, we explain how certificates and the public key infrastructure (PKI) are used in IoT security.

Microservice security is too hard. We must issue and rotate TLS certificates, deploy identity providers, and embed auth logic in applications. These all require secure development, test, and maintenance effort. Istio (a Google, IBM, and Lyft project) offers a new way: by providing a service mesh and a unified identity for each request, it offers all these things with zero application changes.
In this talk we detail:
- What a service mesh is, and why Istio could revolutionise microservices
- Increasing application security and availability using network RBAC and circuit breakers
- Why all applications should use encryption by default
- “Free” mutual TLS between all services and rotate certs every hour
- Preventing token replay attacks that plague JWT
- Securely delegating requests between microservices
https://2018.bris.tech/service-mesh-network-security/

To get this project in ONLINE or through TRAINING Sessions, Contact: JP INFOTECH, 45, KAMARAJ SALAI, THATTANCHAVADY, PUDUCHERRY-9
Landmark: Opposite to Thattanchavady Industrial Estate, Next to VVP Nagar Arch.
Mobile: (0) 9952649690 , Email: [email protected], web: www.jpinfotech.org
Blog: www.jpinfotech.blogspot.com
Detection and Localization of Multiple Spoofing Attackers in Wireless Networks
Wireless spoofing attacks are easy to launch and can significantly impact the performance of networks. Although the identity of a node can be verified through cryptographic authentication, conventional security approaches are not always desirable because of their overhead requirements. In this paper, we propose to use spatial information, a physical property associated with each node, hard to falsify, and not reliant on cryptography, as the basis for 1) detecting spoofing attacks; 2) determining the number of attackers when multiple adversaries masquerading as the same node identity; and 3) localizing multiple adversaries. We propose to use the spatial correlation of received signal strength (RSS) inherited from wireless nodes to detect the spoofing attacks. We then formulate the problem of determining the number of attackers as a multiclass detection problem. Cluster-based mechanisms are developed to determine the number of attackers. When the training data are available, we explore using the Support Vector Machines (SVM) method to further improve the accuracy of determining the number of attackers. In addition, we developed an integrated detection and localization system that can localize the positions of multiple attackers. We evaluated our techniques through two test beds using both an 802.11 (WiFi) network and an 802.15.4 (ZigBee) network in two real office buildings. Our experimental results show that our proposed methods can achieve over 90 percent Hit Rate and Precision when determining the number of attackers. Our localization results using a representative set of algorithms provide strong evidence of high accuracy of localizing multiple adversaries.

JD COLLEGE OF ENGINEERING AND MANAGEMENT (JDCOEM) ETC/EN Final Year Project 2016-2017
RASHMI JUNGHARE
REKHA SONKUSARE
ASHWINI THAKRE
PAYAL DESHMUKH
COMPONENTS:-
1) Microcontroller
2) Finger print sensor
3) Relay
4) Buzzer/ Siren
5) Key
6) Lcd
7) Motor driver
8) Dc Motor RS232
WORKING:-
1) To operate this project first we have to operate this project in this mode we have to enter data into the database of finger print sensor, for this we have to take impressions of fingerprints of that person whom we want to give access to our security system.
2)
This can be done once or whenever a new entry has to be added in the system. Then this project has to be used in In this mode the system compares the fingerprint input received at its optical plate with the previously stored fingerprint from its flash memory.
3) If the entry matches with the memory then it gives out ok signal along with the identity number of that person. But if the entry does not match with the memory then it gives out error signal.
4) The output received from fingerprint sensor is given to the microcontroller. Microcontroller then compares these output data. Function of microcontroller is to turn on the respective device depending upon the input received.
5) In case of OK signal from fingerprint module, microcontroller turns on Relay and a Motor. However if the error output is received then it turns on the Buzzer.

Recorded: 01/26/2011
CERIAS Security Seminar at Purdue University
User and Machine Authentication and Authorization Infrastructure for Distrib...
Torsten Braun, University of Bern
The Wisebed wireless sensor network testbed provides a federated experimentation facility covering several European universities. For scalable management of access control we have designed and implemented a single-sign-on and attribute-based authentication and authorization infrastructure based on the Shibboleth software, which has been developed by the Internet2 Middleware Initiative. Shibboleth is usually used for protecting browser-based access of web resources. We have designed and implemented an extension to protect web services using the Simple Object Access Protocol. This extension allows both user and machine authentication for web services. As a proof of concept, we implemented a complete reservation system for sensor nodes in the Wisebed test-bed federation. Two different user interfaces based on a web page and an iPhone application have been implemented. Although implemented for Shibboleth, the architecture can be easily adapted to other authentication and authorization infrastructures.
Torsten Braun got his Ph.D. degree from University of Karlsruhe (Germany) in 1993. From 1994 to 1995 he has been a guest scientist at INRIA Sophia-Antipolis (France). From 1995 to 1997 he has been working at the IBM European Networking Centre Heidelberg (Germany) as a project leader and senior consultant. He has been a full professor of Computer Science at the University of Bern (Switzerland) since 1998 and director of the Institute of Computer Science and Applied Mathematics at University of Bern since 2007. He has been member of the SWITCH (Swiss education and research network) board of trustees since 2001. (Visit: www.cerias.purude.edu)

This talk will show a very common weakness in RSA signatures. We will be able to computationally extract public RSA keys from communications and embedded systems in case the public key is voluntarily not published. This weakens RSA signatures where keys of small sizes and/or quality are used and allows direct factoring attacks. 2 studies will be conducted on PGP/GPG e-mails and on the Vigik access control system which protects access to nearly 1 million buildings in France.
Bio:
Renaud Lifchitz is a French senior IT security consultant. He has a solid penetration testing, training and research background. His main interests are protocol security (authentication, cryptography, protocol security, information leakage, zero-knowledge proof, RFID security) and number theory. He currently mostly works on wireless protocols and was speaker for the following international conferences: CCC 2010 (Germany), Hackito Ergo Sum 2010 & 2012 (France), DeepSec 2012 (Austria), Shakacon 2012 (USA), 8dot8 2013 (Chile)

Recorded at AppSecUSA 2016 in Washington, DC
https://2016.appsecusa.org/
Patterns of Authentication and Self-Announcement in the Internet of Things (IoT)
The need to connect ‘things’ to each other in the IoT ecosystem introduces new security requirements for authentication and self-announcement due to four major characteristics of IoT
1. Physical access and infinite time available to adversaries to take apart devices
2. Lower computation power of standalone devices
3. Unforeseen and emergent behavior of the system if arbitrary nodes are compromised
4. Endless possibility of privacy intrusion based on data intelligence and indirect identity inference.
In this work the IoT systems are modelled using a number of elements: person, machine/device, service, server, client (esp. mobile), and passive marker. New authentication scenarios emerge when these items introduce themselves to each other on trusted or untrusted networks. The majority of authentication and self-announcement needs could be modelled using the above elements. For major authentication and self-announcement scenarios, possible authentication patterns are presented. Here are four examples of how these patterns apply to sample IoT scenarios:
• Home automation as enabled by NEST devices
• Device collaboration in Zigbee-based networks
• Smart inventory management using NFC/RFID
• Remote device control based on XMPP (SASL authentication)
The minimum computation power (capability to perform cryptographic operations) and privacy preserving considerations are analyzed in each case.
Farbod H Foomany
A senior application security researcher (technical lead) at security compass. He has a bachelor degree in electrical engineering (control systems), Masters degree in artificial intelligence and robotics, and has completed a PhD with main research on security aspects of using voice-print and other biometrics in criminological and security applications. Farbod is currently involved in a project that aims to investigate and formulate the security requirements of system design/development in the internet of things (IoT) ecosystem. Farbod has published and presented his work on signal processing and security in several conferences and journals such IEEE conferences/journals, ISACA journal, crime science conferences and crime reduction networks.
Amir Pourafshar
Application Security Researcher, Security Compass
Amir Pourafshar is an application security researcher at Security Compass. Amir is currently part of a research team working on an IoT project that aims to investigate and formulate the security requirements of system design/development in internet of things (IoT) ecosystem. Amir has done his masters in computer science at Information Security Centre of eXcellence (University of New Brunswick).
-
Managed by the official OWASP Media Project https://www.owasp.org/index.php/OWASP_Media_Project

People carry out digital commerce through a multiplicity of connected devices on the Internet of Things. Location, voice, face, gait and combination of factors are already being used to rapidly recognize and authenticate individuals so that they can carry out everyday commerce. In this session, industry experts discuss the opportunities and constraints surrounding ubiquitous, constant authentication.
Speakers:
Chuck Buffum, VP Business Development, Knurld
Tristan Prince , Online Fraud Prevention Specialist, iovation
Dan Miller, Lead Analyst & Founder, Opus Research

https://discoverdev.io is a site that curates the best developer resources around.
Visit our website for more and signup to our mailing list!
----------
Recorded at AppSecUSA 2016 in Washington, DC
https://2016.appsecusa.org/
Patterns of Authentication and Self-Announcement in the Internet of Things (IoT)
The need to connect ‘things’ to each other in the IoT ecosystem introduces new security requirements for authentication and self-announcement due to four major characteristics of IoT
1. Physical access and infinite time available to adversaries to take apart devices
2. Lower computation power of standalone devices
3. Unforeseen and emergent behavior of the system if arbitrary nodes are compromised
4. Endless possibility of privacy intrusion based on data intelligence and indirect identity inference.
In this work the IoT systems are modelled using a number of elements: person, machine/device, service, server, client (esp. mobile), and passive marker. New authentication scenarios emerge when these items introduce themselves to each other on trusted or untrusted networks. The majority of authentication and self-announcement needs could be modelled using the above elements. For major authentication and self-announcement scenarios, possible authentication patterns are presented. Here are four examples of how these patterns apply to sample IoT scenarios:
• Home automation as enabled by NEST devices
• Device collaboration in Zigbee-based networks
• Smart inventory management using NFC/RFID
• Remote device control based on XMPP (SASL authentication)
The minimum computation power (capability to perform cryptographic operations) and privacy preserving considerations are analyzed in each case.
Farbod H Foomany
A senior application security researcher (technical lead) at security compass. He has a bachelor degree in electrical engineering (control systems), Masters degree in artificial intelligence and robotics, and has completed a PhD with main research on security aspects of using voice-print and other biometrics in criminological and security applications. Farbod is currently involved in a project that aims to investigate and formulate the security requirements of system design/development in the internet of things (IoT) ecosystem. Farbod has published and presented his work on signal processing and security in several conferences and journals such IEEE conferences/journals, ISACA journal, crime science conferences and crime reduction networks.
Amir Pourafshar
Application Security Researcher, Security Compass
Amir Pourafshar is an application security researcher at Security Compass. Amir is currently part of a research team working on an IoT project that aims to investigate and formulate the security requirements of system design/development in internet of things (IoT) ecosystem. Amir has done his masters in computer science at Information Security Centre of eXcellence (University of New Brunswick).
-
Managed by the official OWASP Media Project https://www.owasp.org/index.php/OWASP_Media_Project

Near-field communication (NFC) is a set of communication protocols that enable two electronic devices, one of which is usually a portable device such as a smartphone, to establish communication by bringing them within 4 cm (1.6 in) of each other.[1]
NFC devices are used in contactless payment systems, similar to those used in credit cards and electronic ticket smartcards and allow mobile payment to replace/supplement these systems. This is sometimes referred to as NFC/CTLS (Contactless) or CTLS NFC. NFC is used for social networking, for sharing contacts, photos, videos or files.[2] NFC-enabled devices can act as electronic identity documents and keycards.[3] NFC offers a low-speed connection with simple setup that can be used to bootstrap more capable wireless connections.
Similar ideas in advertising and industrial applications were not generally successful commercially, outpaced by technologies such as barcodes and UHF RFID tags. NFC protocols established a generally supported standard. When one of the connected devices has Internet connectivity, the other can exchange data with online services.
NFC-enabled portable devices can be provided with application software, for example to read electronic tags or make payments when connected to an NFC-compliant apparatus. Earlier close-range communication used technology that was proprietary to the manufacturer, for applications such as stock ticket, access control and payment readers.
Like other "proximity card" technologies, NFC employs electromagnetic induction between two loop antennas when NFC-enabled devices—for example a smartphone and a printer—exchange information, operating within the globally available unlicensed radio frequency ISM band of 13.56 MHz on ISO/IEC 18000-3 air interface at rates ranging from 106 to 424 kbit/s.
Each full NFC device can work in three modes:
NFC card emulation—enables NFC-enabled devices such as smartphones to act like smart cards, allowing users to perform transactions such as payment or ticketing.
NFC reader/writer—enables NFC-enabled devices to read information stored on inexpensive NFC tags embedded in labels or smart posters.
NFC peer-to-peer—enables two NFC-enabled devices to communicate with each other to exchange information in an adhoc fashion.
NFC tags are passive data stores which can be read, and under some circumstances written to, by an NFC device. They typically contain data (as of 2015 between 96 and 8,192 bytes) and are read-only in normal use, but may be rewritable. Applications include secure personal data storage (e.g. debit or credit card information, loyalty program data, personal identification numbers (PINs), contacts). NFC tags can be custom-encoded by their manufacturers or use the industry specifications.
The standards were provided by the NFC Forum.[4] The forum was responsible for promoting the technology and setting standards and certifies device compliance. Secure communications are available by applying encryption algorithms as is done for credit cards[5] and if they fit the criteria for being considered a personal area network.[citation needed]
NFC standards cover communications protocols and data exchange formats and are based on existing radio-frequency identification (RFID) standards including ISO/IEC 14443 and FeliCa.[6] The standards include ISO/IEC 18092[7] and those defined by the NFC Forum. In addition to the NFC Forum, the GSMA group defined a platform for the deployment of GSMA NFC Standards[8] within mobile handsets. GSMA's efforts include Trusted Services Manager,[9] Single Wire Protocol, testing/certification and secure element.[10]
A patent licensing program for NFC is under deployment by France Brevets, a patent fund created in 2011. This program was under development by Via Licensing Corporation, an independent subsidiary of Dolby Laboratories, and was terminated in May 2012.[citation needed] A platform-independent free and open source NFC library, libnfc, is available under the GNU Lesser General Public License.

Detection and Localization of Multiple Spoofing Attackers in Wireless Networks 2012 IEEE DOTNET
TO GET THIS PROJECT IN ONLINE OR THROUGH TRAINING SESSIONS CONTACT:
Chennai Office: JP INFOTECH, Old No.31, New No.86, 1st Floor, 1st Avenue, Ashok Pillar, Chennai – 83. Landmark: Next to Kotak Mahendra Bank / Bharath Scans.
Landline: (044) - 43012642 / Mobile: (0)9952649690
Pondicherry Office: JP INFOTECH, #45, Kamaraj Salai, Thattanchavady, Puducherry – 9. Landmark: Opp. To Thattanchavady Industrial Estate & Next to VVP Nagar Arch.
Landline: (0413) - 4300535 / Mobile: (0)8608600246 / (0)9952649690
Email: [email protected],
Website: http://www.jpinfotech.org,
Blog: http://www.jpinfotech.blogspot.com
Wireless spoofing attacks are easy to launch and can significantly impact the performance of networks. Although the identity of a node can be verified through cryptographic authentication, conventional security approaches are not always desirable because of their overhead requirements. In this paper, we propose to use spatial information, a physical property associated with each node, hard to falsify, and not reliant on cryptography, as the basis for (1) detecting spoofing attacks; (2) determining the number of attackers when multiple adversaries masquerading as a same node identity; and (3) localizing multiple adversaries. We propose to use the spatial correlation of received signal strength (RSS) inherited from wireless nodes to detect the spoofing attacks. We then formulate the problem of determining the number of attackers as a multi-class detection problem. Cluster-based mechanisms are developed to determine the number of attackers. When the training data is available, we explore using Support Vector Machines (SVM) method to further improve the accuracy of determining the number of attackers. In addition, we developed an integrated detection and localization system that can localize the positions of multiple attackers. We evaluated our techniques through two testbeds using both an 802.11 (WiFi) network and an 802.15.4 (ZigBee) network in two real office buildings. Our experimental results show that our proposed methods can achieve over 90% Hit Rate and Precision when determining the number of attackers. Our localization results using a representative set of algorithms provide strong evidence of high accuracy of localizing multiple adversaries.

📖📕 GET THE NEW TINKERNUT BOOK: http://bit.ly/Tinkernutbook 📕📖
UPDATE: The MacMakeup website is down. You can download now download it from this link:
http://www.tinkernut.com/demos/205_mac/macmakeup195d.zip
This video will show you how to bypass websites that have blocked you by changing your MAC address, which will change your IP address

Live from Syracuse University's Center of Excellence (SyracuseCoE), this webinar featured a presentation by Scott Wu, chief executive officer of NewSky Security and Richard Yim, vice president of product management with People Power Company. Wu and Yim discussed emerging threats due to the proliferation of the Internet of Things (IoT) landscape and connected devices in the home, offices, and major industrial centers. Associate Director of Research at SyracuseCoE Chetna Chianese introduced the webinar with an overview of the SyracuseCoE.

To get this project in ONLINE or through TRAINING Sessions, Contact: JP INFOTECH, 45, KAMARAJ SALAI, THATTANCHAVADY, PUDUCHERRY-9
Landmark: Opposite to Thattanchavady Industrial Estate, Next to VVP Nagar Arch.
Mobile: (0) 9952649690 , Email: [email protected], web: www.jpinfotech.org
Blog: www.jpinfotech.blogspot.com
Detection and Localization of Multiple Spoofing Attackers in Wireless Networks NS2 2013 IEEE
Wireless spoofing attacks are easy to launch and can significantly impact the performance of networks. Although the identity of a node can be verified through cryptographic authentication, conventional security approaches are not always desirable because of their overhead requirements. In this paper, we propose to use spatial information, a physical property associated with each node, hard to falsify, and not reliant on cryptography, as the basis for 1) detecting spoofing attacks; 2) determining the number of attackers when multiple adversaries masquerading as the same node identity; and 3) localizing multiple adversaries. We propose to use the spatial correlation of received signal strength (RSS) inherited from wireless nodes to detect the spoofing attacks. We then formulate the problem of determining the number of attackers as a multiclass detection problem. Cluster-based mechanisms are developed to determine the number of attackers. When the training data are available, we explore using the Support Vector Machines (SVM) method to further improve the accuracy of determining the number of attackers. In addition, we developed an integrated detection and localization system that can localize the positions of multiple attackers. We evaluated our techniques through two test beds using both an 802.11 (WiFi) network and an 802.15.4 (ZigBee) network in two real office buildings. Our experimental results show that our proposed methods can achieve over 90 percent Hit Rate and Precision when determining the number of attackers. Our localization results using a representative set of algorithms provide strong evidence of high accuracy of localizing multiple adversaries.

Come see the future of IoT connectivity, hear about Thread, and learn how you can use IoT Core connect to directly low power devices with no gateways in between. Thread works just like WiFi devices and is a short range, low power, mesh networking standard that Google helped pioneer. This session will cover enabling CoAP in Cloud IoT Core, building and deploying code to embedded devices running the OpenThread stack, and creating a simple application to view data and control the devices.
Watch more #io19 here: IoT at Google I/O 2019 Playlist → https://goo.gle/2ITYqih
GCP at Google I/O 2019 Playlist → https://goo.gle/2ZPLejw
Google I/O 2019 All Sessions Playlist → https://goo.gle/io19allsessions
Learn more on the I/O Website → https://google.com/io
Subscribe to the Google Cloud Platform Channel → https://goo.gle/GCP
Get started at → https://cloud.google.com/gcp
Speaker(s): Calum Barnes, Jonathan Hui
T472DE

To get this project in ONLINE or through TRAINING Sessions, Contact: JP INFOTECH, 45, KAMARAJ SALAI, THATTANCHAVADY, PUDUCHERRY-9
Landmark: Opposite to Thattanchavady Industrial Estate, Next to VVP Nagar Arch.
Mobile: (0) 9952649690 , Email: [email protected], web: www.jpinfotech.org
Blog: www.jpinfotech.blogspot.com
Detection and Localization of Multiple Spoofing Attackers in Wireless Networks JAVA
Wireless spoofing attacks are easy to launch and can significantly impact the performance of networks. Although the identity of a node can be verified through cryptographic authentication, conventional security approaches are not always desirable because of their overhead requirements. In this paper, we propose to use spatial information, a physical property associated with each node, hard to falsify, and not reliant on cryptography, as the basis for 1) detecting spoofing attacks; 2) determining the number of attackers when multiple adversaries masquerading as the same node identity; and 3) localizing multiple adversaries. We propose to use the spatial correlation of received signal strength (RSS) inherited from wireless nodes to detect the spoofing attacks. We then formulate the problem of determining the number of attackers as a multiclass detection problem. Cluster-based mechanisms are developed to determine the number of attackers. When the training data are available, we explore using the Support Vector Machines (SVM) method to further improve the accuracy of determining the number of attackers. In addition, we developed an integrated detection and localization system that can localize the positions of multiple attackers. We evaluated our techniques through two test beds using both an 802.11 (WiFi) network and an 802.15.4 (ZigBee) network in two real office buildings. Our experimental results show that our proposed methods can achieve over 90 percent Hit Rate and Precision when determining the number of attackers. Our localization results using a representative set of algorithms provide strong evidence of high accuracy of localizing multiple adversaries.

To get this project in ONLINE or through TRAINING Sessions, Contact:JP INFOTECH, Old No.31, New No.86, 1st Floor, 1st Avenue, Ashok Pillar, Chennai -83.
Landmark: Next to Kotak Mahendra Bank.
Pondicherry Office: JP INFOTECH, #45, Kamaraj Salai, Thattanchavady, Puducherry -9.
Landmark: Next to VVP Nagar Arch.
Mobile: (0) 9952649690 , Email: [email protected], web: www.jpinfotech.org
Blog: www.jpinfotech.blogspot.com
Cooperative Caching for Efficient Data Access in Disruption Tolerant Networks
Disruption tolerant networks (DTNs) are characterized by low node density, unpredictable node mobility, and lack of global network information. Most of current research efforts in DTNs focus on data forwarding, but only limited work has been done on providing efficient data access to mobile users. In this paper, we propose a novel approach to support cooperative caching in DTNs, which enables the sharing and coordination of cached data among multiple nodes and reduces data access delay. Our basic idea is to intentionally cache data at a set of network central locations (NCLs), which can be easily accessed by other nodes in the network. We propose an efficient scheme that ensures appropriate NCL selection based on a probabilistic selection metric and coordinates multiple caching nodes to optimize the tradeoff between data accessibility and caching overhead. Extensive trace-driven simulations show that our approach significantly improves data access performance compared to existing schemes.

IOT Chain ICO Review - December 20, 2017
Today I look at IOT chain a new ICO check out the specifics down below - * IOTA Blockchain of China
Advantages
* Strong investors (FBG)
* Strong comparable with IOTA at $12bn
* Little advertising so far
* Partnerships with
* Shanghai High flying electronics technology
* Peoples daily digital communication
* Shenzhen Galaxywind Network system
* Shanghai Shuncom Smart Technology
* Telink semiconductor
* Shanghai BeTiger Network Technology
* Shenzhen LEnze Technology
Why is it Important?
* Security
* IOT is susceptible to botnet attacks
* Cost
* IOT has a high cost of centralised architecture
* Maintaining the centralised cloud and large scale serve cluster is very expensive
Core technology
* Asymmetrical encryption
* ITC nodes protect the users privacy
* The blockchain cannot be tampered with
* Scalability
* The future ITC will have tens of thousands of nodes to meet the needs of IOT data storage with the blockchain.
* Consensus system
* PBFT consensus, the DAG network
官网/Website
https://iotchain.io/
白皮书/Whitepaper
https://iotchain.io/pdf/web/ITCWHITEPAPER.pdf
Telegram
https://t.me/IoTChain
GitHub
https://github.com/IoTChainCode
Twitter:
https://twitter.com/IoT_Chain
Bitcoin Talk Genesis:
https://bitcointalk.org/index.php?topic=2612309.new#new
Disclaimer
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We strongly encourage all investors to conduct their own research before making any investment decision. For more information on stock market investing, visit the Securities and Exchange Commission ("SEC") at www.sec.gov.

While risk mitigation for cybersecurity in healthcare has improved over the last few years, there is still a long way to go. After the recent impact of the Wanna Cry ransomware attacks on the United Kingdom's National Health Service, US Congressional leaders are calling for hearings on the capabilities of the US healthcare system to withstand cyber attacks. At the same time, consumers are becoming increasingly concerned about the security of their personal medical information yet pushing for better user experiences with their insurance companies and medical providers. This all means increased risk and costs for healthcare companies.
Meanwhile, the nature of authentication is changing. Traditional binary authentication (username & password) presents a number of security risks and usability impacts. But, what are the alternative? During this session, you will hear from FIDO Alliance member and healthcare leader, Aetna on how they are deploying next generation authentication across their mobile and web applications.

www.startechnologychennai.com
+91 8870457435
E mail Id - startechnologychennai.com
We are supporting Omnet++ phd & masters project in IOT enabled in LTE Network.
Abstract:
The Evolved Packet System-based Authentication and Key Agreement (EPS-AKA) protocol of the long-
term evolution (LTE) network does not support Internet of Things (IoT) objects and has several security
limitations, including transmission of the object’s (user/device) identity and key set identifier in plaintext over
the network, synchronization, large overhead, limited identity privacy, and security attack vulnerabilities.
In this article, we propose a new secure and efficient AKA protocol for the LTE network that supports
secure and efficient communications among various IoT devices as well as among the users. Analysis shows
that our protocol is secure, efficient, and privacy preserved, and reduces bandwidth consumption during
authentication.

Dictionary Based Secure Provenance Compression for Wireless Sensor Networks in Java
To get this project in Online or through training sessions Contact:
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Due to energy and bandwidth limitations of wireless sensor networks (WSNs), it is crucial that data provenance for these networks be as compact as possible. Even if lossy compression techniques are used for encoding provenance information, the size of the provenance increases with the number of nodes traversed by the network packets. To address such issues, we propose a dictionary based provenance scheme. In our approach, each sensor node in the network stores a packet path dictionary. With the support of this dictionary, a path index instead of the path itself is enclosed with each packet. Since the packet path index is a code word of a dictionary, its size is independent of the number of nodes present in the packet’s path. Furthermore, as our scheme binds the packet and its provenance through an AM-FM sketch and uses a secure packet sequence number generation technique, it can defend against most of the known provenance attacks. Through simulation and experimental results, we show that our scheme outperforms other compact provenance schemes with respect to provenance size, robustness, and energy consumption.

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Speaker: Robert Clark, Cybersecurity and Communications, Department of Homeland Security
This presentation reviews the important legal opinions and law review articles of the past year that affect privacy as it relates to the internet and computer network operations. We will review the cases and legal commentaries on those issues that most affect your conduct and business operations. This presentation is strongly audience driven and it quickly becomes an open forum for questions and debate.
This year the past key precedents have involved: work place monitoring and searches; compliance with State data breach laws and jurisdiction; employer's right to monitor their computer network systems and employees' rights; acceptable use policies; banners; user agreements; personally identifiable information and IP addresses; what is personally identifiable information; privacy and social networks; privacy rights in information turned over to a third party; theft of proprietary information and the CFAA; and, web site policies and notice.
For more information and presentation slides click here: http://bit.ly/8XJ1tm

This presentation will dive into research, outcomes, and recommendations regarding information security for the "Internet of Things". Mark and Zach will discuss IoT security failures both from their own research as well as the work of people they admire. Attendees are invited to laugh/cringe at concerning examples of improper access control, a complete lack of transport security, hardcoded-everything, and ways to bypass paying for stuff.